TY  - BOOK
AU  - Dastres,Roza
AU  - Yurtkan,Kamil
TI  - MASKED FACE RECOGNITION
PY  - 2022///
KW  - Human face recognition (Computer science)
KW  - Dissertations, Academic
N1  - Thesis (MSc) - Cyprus International University. Institute of Graduate Studies and Research Information Technology Department; Includes bibliography (sheets 56-63)
N2  - ABSTRACT
Face biometrics have been recognized as a feature for identification for many years, 
and most researchers and scholars recognize these biometrics as one of the most 
reliable and accurate biometrics. But in recent years, these biometrics have been used 
to identify other human characteristics such as age, race, gender, and so on. Regarding 
the vast range of applications for facial recognition in identification, significant 
research has been done in this field, although it falls short of ideals. With the advent 
of COVID19 at the end of the twentieth century, the challenge of masking face 
recognition was created. According to extensive research on face research in this field, 
existing face-based identification methods have received less attention in various mask 
challenges. The primary goal of this research is to find answers to the following 
questions of masked face recognition systems. Therefore, it is necessary to invent a 
method that has a good response to stable changes and time, in order to recognize the 
masked faces. This study uses a "Real World Masked Face Dataset" image database. 
The method presented in this research, after preprocessing, Morphological Operations 
has been utilized to derive features from pictures of people's faces by using the KNN 
descriptors. To classify the properties extracted by the descriptors, two families of 
super plane and neighborhood classifiers k are the nearest neighbors.
Finally, after implementing the ideas considered in the employed method and 
comparing the results of the classification, 72.5% for the desired database for 
classification with k nearest neighbor have been obtained for classification.
Keywords: Masked Face Recognition, Face Biometric
ER  -